import requests #204 for number of responses with the exclusion

root = 'https://collectionapi.metmuseum.org'
path = '/public/collection/v1/search'
parameter = '?q=fat&'

root+path+parameter

'https://collectionapi.metmuseum.org/public/collection/v1/search?q=fat&'

Mresponse = requests.get(root+path+parameter)

Mresponse

<Response [200]>

mparsed=Mresponse.json()

mparsed.keys()

dict_keys(['total', 'objectIDs'])

objectids = mparsed['objectIDs']

len(objectids)

272

objects = 'public/collection/v1/objects/'

results=[]

for i in objectids:
  url = f'https://collectionapi.metmuseum.org/public/collection/v1/objects/{i}'
  response = requests.get(url) #variables usually stay in the loop
  parsed = response.json()
  results.append(parsed)
    # if response.status_code == 200:
    # parsed = response.json()
    # results.append(parsed)

results[0]

{'objectID': 544510,
 'isHighlight': False,
 'accessionNumber': '17.10.2',
 'accessionYear': '1917',
 'isPublicDomain': True,
 'primaryImage': 'https://images.metmuseum.org/CRDImages/eg/original/17.10.2_EGDP011882.jpg',
 'primaryImageSmall': 'https://images.metmuseum.org/CRDImages/eg/web-large/17.10.2_EGDP011882.jpg',
 'additionalImages': [],
 'constituents': None,
 'department': 'Egyptian Art',
 'objectName': 'Jar Label, fat',
 'title': 'Hieratic Jar Label',
 'culture': '',
 'period': 'New Kingdom',
 'dynasty': 'Dynasty 18',
 'reign': 'reign of Amenhotep III',
 'portfolio': '',
 'artistRole': '',
 'artistPrefix': '',
 'artistDisplayName': '',
 'artistDisplayBio': '',
 'artistSuffix': '',
 'artistAlphaSort': '',
 'artistNationality': '',
 'artistBeginDate': '',
 'artistEndDate': '',
 'artistGender': '',
 'artistWikidata_URL': '',
 'artistULAN_URL': '',
 'objectDate': 'ca. 1390–1353 B.C.',
 'objectBeginDate': -1390,
 'objectEndDate': -1390,
 'medium': 'Pottery',
 'dimensions': 'H. 24 × W. 23 × Dia. 9.5 × Th. 0.7 cm (9 7/16 × 9 1/16 × 3 3/4 × 1/4 in.)',
 'measurements': [{'elementName': 'Overall',
   'elementDescription': None,
   'elementMeasurements': {'Diameter': 9.5,
    'Height': 24,
    'Thickness': 0.7,
    'Width': 23}}],
 'creditLine': 'Rogers Fund, 1917',
 'geographyType': 'From',
 'city': '',
 'state': '',
 'county': '',
 'country': 'Egypt',
 'region': 'Upper Egypt, Thebes',
 'subregion': 'Malqata',
 'locale': 'House 3 W',
 'locus': '',
 'excavation': 'MMA excavations',
 'river': '',
 'classification': '',
 'rightsAndReproduction': '',
 'linkResource': '',
 'metadataDate': '2024-10-03T04:53:53.567Z',
 'repository': 'Metropolitan Museum of Art, New York, NY',
 'objectURL': 'https://www.metmuseum.org/art/collection/search/544510',
 'tags': [{'term': 'Hieratic',
   'AAT_URL': 'http://vocab.getty.edu/page/aat/300206211',
   'Wikidata_URL': 'https://www.wikidata.org/wiki/Q208111'}],
 'objectWikidata_URL': 'https://www.wikidata.org/wiki/Q116247690',
 'isTimelineWork': False,
 'GalleryNumber': '119'}

METfw = [] # Met Fat Works

for item in results:
  if 'title' in item:
    METfw.append(item['title'])
  else:
    METfw.append('no title')

len(METfw) # IDs, titles, descriptions, dates, nationality, medium/format, genders, and image links

272

# Create a new list that includes all items from my_list except for the value 3
met_titles = [item for item in METfw if item not in ['Jar Label', 'Wig', 'Bowl',
                                                   'Candlestick',
                                                   'Clay jar sealing',
                                                   'Jar Sealing',
                                                   'Fat Jar Label',
                                                   'Kohl Tube',
                                                   'Staff',
                                                   'Jar Label Type 140.1',
                                                   'Brush holder  in shape of bamboo',
                                                   'Ointment Jar',
                                                   'Kohl Container Decorated with Bes-images',
                                                   'Floral Garlands of Nauny',
                                                   'Club',
                                                   'Jar label fragment']]
print(met_titles)

['Hieratic Jar Label', 'Bowl of Fat', 'Gilt bronze ring', 'Terracotta aryballos (perfume vase) in the form of a boy', 'Vase', 'Dragon', 'Landscapes', 'Fat conical vase', 'Offering table from the mortuary temple of Amenemhat I', '', 'Figurine of a Seated Woman', 'The Entombment of Christ', 'Upper part of a male seated figure', 'Orchid Pavilion Gathering; Autumn Harvest Festival', 'Bronze statuette of a philosopher on a lamp stand', 'Bust of an Official', 'The Old Duchess', 'Child god wearing Amonian crown and named Horus of Mednit (Aphroditopolis)', 'Les Paul prototype recording model, serial no. 001', 'Drum', 'Drop-front desk (secrétaire à abattant or secrétaire en cabinet)', 'The Wedding of Stephen Beckingham and Mary Cox', 'Relief of Hatiay', 'Trade card from the Fat and Skinny Their Little Pup Too series (W500)', 'Model Cattle stable from the tomb of Meketre', 'Isis and Horus', 'Two Fat Peasant Women', 'Jar, Fat Figure', 'Jar, Fat Figure', 'Netsuke of Mask; Fat-Faced Girl and Demon', 'An old skinny man at left talking with a fat man at right', 'The Fat Kitchen, from the series Monkeys', 'A Fat Man Confronting a Thin Man', 'Trade card from the Fat and Skinny Their Little Pup Too series (W500)', 'Trade card from the Fat and Skinny Their Little Pup Too series (W500)', 'Trade card from the Fat and Skinny Their Little Pup Too series (W500)', 'Trade card from the Fat and Skinny Their Little Pup Too series (W500)', 'Trade card from the Fat and Skinny Their Little Pup Too series (W500)', 'Trade card from the Fat and Skinny Their Little Pup Too series (W500)', 'Trade card from the Fat and Skinny Their Little Pup Too series (W500)', 'Trade card from the Fat and Skinny Their Little Pup Too series (W500)', 'Trade card from the Fat and Skinny Their Little Pup Too series (W500)', 'Trade card from the Fat and Skinny Their Little Pup Too series (W500)', 'Trade card from the Fat and Skinny Their Little Pup Too series (W500)', 'Funerary mask of Hatnefer', 'Bust of a deformed man with a hat and a fat, protruding lower lip in profile to left', 'Four Caterpillars and a Snail', "Looking at a Manet painting, from 'Sketches from the Salon,' published in Le Charivari, June 19, 1865", 'Relief Depicting Meryneith Inspecting His Stables and Ships Unloading Merchandise, from his tomb at Saqqara', 'Fragment of decree of Horus Khabau, probably King Neferkaure', 'Bronze chariot inlaid with ivory', 'Untitled', 'Caricature of a Fat Man, Seen From Behind', 'Caricature of a Fat Person Wearing a Long Cloak and a Tricorne, Seen from Behind', 'Fat Couple and Little Shaggy Dog, from 347 Suite', 'Fat Prostitute and Musketeer, from 347 Suite', 'Fat Courtesan Greeted by Three Gentlemen, from 347 Suite', 'Fat Courtesan and Old Beau, from 347 Suite', 'The Fat Kitchen', 'Venerable Idleness, Queen of Cockaigne; a fat woman seated on a movable toilet chair being waited on and fed by seven women', 'Entry, or Lord Fat Cheeks (Entrée, ou Milord-Gorju)', 'Cooking Cakes with Fat, Tomb of Rekhmire', 'Fat man at a carnival, Md.', 'English Exhibitions in Paris or French People Astonished at Our Improvement in the Breed of Fat Cattle', 'Cries of London, No. 2: Buy my Goose, my fat Goose', 'English Exhibitions in Paris or French People Astonished at Our Improvement in the Breed of Fat Cattle', 'Fat girl yawning, N.Y.C.', 'Pot Fair Cambridge, and, The College Gate', 'Fragment of a labeled jar containing fat', 'Pot Fair Cambridge', 'The Parable of the Prodigal Son, No. IV: The Fatted Calf', 'Broadside with 48 scenes illusrating  the misfortunes of a fat man', "Too fat, from 'News of the day,' published in Le Charivari, November 16, 1867", 'Fat Courtesan with an Old Man and a Spectator in Costume, from 347 Suite', 'The College Gate', 'Novella del Grasso Legnaiuolo', 'Standing boy', 'Statuette of a fat boy (dwarf ?)', 'Terracotta oil lamp', 'Actors at the Hotel de Bourgogne', 'A Sketch from Nature', 'A Sketch from Nature', 'Seated hollow figure with helmet', 'Piece', 'Candlestand (one of a pair)', 'The Great Pyramid, Giza', 'Sprite', 'The Fat Boy (from Side Show)', 'A seated fat lady', 'Glass head-shaped flask', 'Scenes from the Story of Joseph', 'Marble portrait bust of a man', 'George III pattern sovereign with St. George reverse', 'George III pattern sovereign with St. George reverse', 'King Henry IV', 'The Ambassador of Good Will', 'Figure-Celt Pendant', 'Figure: Female (Akua Ba)', 'Glass double head-shaped flask', 'Statuette of Harpokrates', 'Dance of Death in Seven Tempos (Dood - Dans in Zeven Tempos)', 'Figure Vessel', 'The Corsican Spider in His Web!', 'The Corsican Spider in His Web!', 'Four Caterpillars and a Snail', 'The Fat Kitchen, from the series Monkeys', 'Fat Free Surrealism, Curated by Red Grooms', 'Dropsy Courting Consumption', 'Dropsy Courting Consumption', 'Sketchbook of Figure Studies', 'no title', 'Glass double head flask', 'Funerary Mask', 'Bird Pendant', 'Two Female Nudes; Seated Male Nude (after Michelangelo?); Three Equestrian Figures (from Sketchbook)', 'Wavy-handled jar', 'Ground Zero', 'Garbage is valuable', 'The Holy Friar', '[Crowd Viewing "Fat Boy"]', 'Fat Claude and her Girlfriend at Le Monocle', 'This Hog the Property of Mr. William White of Kingston, Surrey...', 'Satyrical Poetry', 'Camp Lakecrest campers walking away, Dutchess County, N.Y.', 'Girl with a plaid shirt at Camp Lakecrest, Dutchess County, N.Y.', 'Vase Nº 2980', 'Girl sitting in the grass at Camp Lakecrest, Dutchess County, N.Y.', 'Girls standing in a line at Camp Lakecrest, Dutchess County, N.Y.', 'Infant Bacchus with Grapes', 'no title', 'Staff with Snuff Vessels', 'Dressing for a Masquerade', 'Dressing for a Masquerade', 'On Tue Le Veau Gras (One Kills The Fat Calf), from "L\'Enfant Prodigue" (The Prodigal Son)', 'On Tue Le Veau Gras (One Kills The Fat Calf), from "L\'Enfant Prodigue" (The Prodigal Son)', "A fat british man in a wig, bound in L'Oeuvre original de Vivant Denon. Collection de eaux-fortes, Volume 2", 'Costumed Figure', 'Girl with a baseball glove at Camp Lakecrest, Dutchess County, N.Y.', 'Transvestite with a torn stocking, N.Y.C.', 'Engraved pearl shell', 'Engraved pearl shell', 'Engraved pearl shell', 'Engraved pearl shell with human hair string', 'Engraved pearl shell', 'Engraved pearl shell', 'Henry on roller skates pushed by a fat man\'s stomach, from the "Little Henry" (T78), issued with Tareyton Cigarettes by the R. J. Reynolds Tobacco Company', 'Nobody Loves a Fat Man, from the "Mutt and Jeff" series (T88), issued with Sweet Caporal Cigarettes by Kinney Brothers Tobacco Company', 'Nobody Loves A Fat Man, from the "Mutt and Jeff" series (T88), issued with Sweet Caporal Cigarettes by Kinney Brothers Tobacco Company', 'Nobody Loves A Fat Man, from the "Mutt and Jeff" series (T88), issued with Sweet Caporal Cigarettes by Kinney Brothers Tobacco Company', 'Prize Fat Cattle', 'The Fat Cow Invaded..., from "Actualités"', 'The Fat Kitchen', '[Alma Mahler Doll Made for Oskar Kokoschka by Hermine Moos]', 'no title', 'Female Fertility Figure (Akuaba)', 'Dressing for a Birthday', 'Dressing for a Birthday', '100 Woodcuts by Posada / 100 Grabados en madera por Posada', "Bull's Head Tavern", '[Five 35mm Film Frames: Subway Passengers, New York City: Two Men in Suits]', '[Five 35mm Film Frames: Subway Passengers, New York City: Two Men in Suits]', '[Five 35mm Film Frames: Subway Passengers, New York City: Two Men in Suits]', 'Night-Shining White', 'Design for a Frontispiece:  Mercury and Fame', 'Engraved pearl shell and hair-string belt (riji, or jakoli, longkalongka)', 'Frenchmen in November', 'Nobody Loves A Fat Man, from the "Mutt and Jeff" series (T88), issued by Kinney Brothers Tobacco Company', 'Nobody Loves A Fat Man, from the "Mutt and Jeff" series (T88),  issued with Sweet Caporal Cigarettes by Kinney Brothers Tobacco Company', 'Nobody Loves A Fat Man, from the "Mutt and Jeff" series (T88),  issued with Sweet Caporal Cigarettes by Kinney Brothers Tobacco Company', 'Openwork furniture plaque showing a cow suckling a calf', 'Bust of a deformed man with a hat and a fat, protruding lower lip in profile to left', 'New Years Greeting showing a table laden with food', 'Itelmen Preparing Fish to be Dried', 'Prayer book with case (mahdar)', 'Headrest', 'Pochette', 'Madonna and Child with Saints Francis and Jerome', 'Copped at a Cock Fight', 'Cain fleeing after having slain Abel', 'In and Out of Condition', 'A Fair Start: "Take de water togedder when yous hear de shot!"', 'Transvestite on a couch, N.Y.C.', 'A Literary Debate in the Darktown Club: The Question Settled', 'Returning Home', 'Courtly Odes, Beginning with "Wild Geese"', 'An Emaciated Horse Led by His Master', 'From Soho', 'From Eaton', 'From Warwick Lane, from "Caricatures of the English"', 'The Darktown Hook and Ladder Corps: In Action', 'The "Bab" Ballads, Much Sound and Little Sense', 'Marble tripod or altar found at Ostia by Gavin Hamilton in 1775, from "Vasi, candelabri, cippi, sarcofagi, tripodi, lucerne, ed ornamenti antichi disegnati ed incisi dal Cav. Gio. Batt. Piranesi, Vol. I" (Vases, candelabra, grave stones, sarcophagi, tripods, lamps, and ornaments designed and etched by Cavalieri Giovanni Battista Piranesi)', 'Plan of the Baths of Diocletian..., tome 1, tavola 42 from "Le Antichità Romane" (Roman Antiquities)', 'Eighteen Songs of a Nomad Flute: The Story of Lady Wenji', 'Room found in 1758 among the ruins of an ancient villa on the Appian Way at Frattochie, near Albano, from which the ancient manner of heating and cooling rooms was discovered [sectional diagram], tavola 26 b from "Antichità d\'Albano e di Castel Gandolfo Descritte ed incise da Giovambatista Piranesi" (Antiquities of Albano and of Castel Gandolfo described and etched by Giovambattista Piranesi)', 'Room found in 1758 among the ruins of an ancient villa on the Appian Way at Frattochie, near Albano, from which the ancient manner of heating and cooling rooms was discovered [sectional diagram], tavola 26 b from "Antichità d\'Albano e di Castel Gandolfo Descritte ed incise da Giovambatista Piranesi" (Antiquities of Albano and of Castel Gandolfo described and etched by Giovambattista Piranesi)', 'Blue Monday', 'Palazzo Pontificio (Palazzo Quirinale)', 'The Darktown Fire Brigade -- Hook and Ladder Gymnastics: "Brace her up dar! and cotch her on de fly!"', 'Redemption – Repudiation : Prosperity – Ruin', 'no title', 'September Morn', 'Prayer Book: Arganonä Maryam (The Organ of Mary)', 'Jack in Office']

len(met_titles)

204

met_titles

['Hieratic Jar Label',
 'Bowl of Fat',
 'Gilt bronze ring',
 'Terracotta aryballos (perfume vase) in the form of a boy',
 'Vase',
 'Dragon',
 'Landscapes',
 'Fat conical vase',
 'Offering table from the mortuary temple of Amenemhat I',
 '',
 'Figurine of a Seated Woman',
 'The Entombment of Christ',
 'Upper part of a male seated figure',
 'Orchid Pavilion Gathering; Autumn Harvest Festival',
 'Bronze statuette of a philosopher on a lamp stand',
 'Bust of an Official',
 'The Old Duchess',
 'Child god wearing Amonian crown and named Horus of Mednit (Aphroditopolis)',
 'Les Paul prototype recording model, serial no. 001',
 'Drum',
 'Drop-front desk (secrétaire à abattant or secrétaire en cabinet)',
 'The Wedding of Stephen Beckingham and Mary Cox',
 'Relief of Hatiay',
 'Trade card from the Fat and Skinny Their Little Pup Too series (W500)',
 'Model Cattle stable from the tomb of Meketre',
 'Isis and Horus',
 'Two Fat Peasant Women',
 'Jar, Fat Figure',
 'Jar, Fat Figure',
 'Netsuke of Mask; Fat-Faced Girl and Demon',
 'An old skinny man at left talking with a fat man at right',
 'The Fat Kitchen, from the series Monkeys',
 'A Fat Man Confronting a Thin Man',
 'Trade card from the Fat and Skinny Their Little Pup Too series (W500)',
 'Trade card from the Fat and Skinny Their Little Pup Too series (W500)',
 'Trade card from the Fat and Skinny Their Little Pup Too series (W500)',
 'Trade card from the Fat and Skinny Their Little Pup Too series (W500)',
 'Trade card from the Fat and Skinny Their Little Pup Too series (W500)',
 'Trade card from the Fat and Skinny Their Little Pup Too series (W500)',
 'Trade card from the Fat and Skinny Their Little Pup Too series (W500)',
 'Trade card from the Fat and Skinny Their Little Pup Too series (W500)',
 'Trade card from the Fat and Skinny Their Little Pup Too series (W500)',
 'Trade card from the Fat and Skinny Their Little Pup Too series (W500)',
 'Trade card from the Fat and Skinny Their Little Pup Too series (W500)',
 'Funerary mask of Hatnefer',
 'Bust of a deformed man with a hat and a fat, protruding lower lip in profile to left',
 'Four Caterpillars and a Snail',
 "Looking at a Manet painting, from 'Sketches from the Salon,' published in Le Charivari, June 19, 1865",
 'Relief Depicting Meryneith Inspecting His Stables and Ships Unloading Merchandise, from his tomb at Saqqara',
 'Fragment of decree of Horus Khabau, probably King Neferkaure',
 'Bronze chariot inlaid with ivory',
 'Untitled',
 'Caricature of a Fat Man, Seen From Behind',
 'Caricature of a Fat Person Wearing a Long Cloak and a Tricorne, Seen from Behind',
 'Fat Couple and Little Shaggy Dog, from 347 Suite',
 'Fat Prostitute and Musketeer, from 347 Suite',
 'Fat Courtesan Greeted by Three Gentlemen, from 347 Suite',
 'Fat Courtesan and Old Beau, from 347 Suite',
 'The Fat Kitchen',
 'Venerable Idleness, Queen of Cockaigne; a fat woman seated on a movable toilet chair being waited on and fed by seven women',
 'Entry, or Lord Fat Cheeks (Entrée, ou Milord-Gorju)',
 'Cooking Cakes with Fat, Tomb of Rekhmire',
 'Fat man at a carnival, Md.',
 'English Exhibitions in Paris or French People Astonished at Our Improvement in the Breed of Fat Cattle',
 'Cries of London, No. 2: Buy my Goose, my fat Goose',
 'English Exhibitions in Paris or French People Astonished at Our Improvement in the Breed of Fat Cattle',
 'Fat girl yawning, N.Y.C.',
 'Pot Fair Cambridge, and, The College Gate',
 'Fragment of a labeled jar containing fat',
 'Pot Fair Cambridge',
 'The Parable of the Prodigal Son, No. IV: The Fatted Calf',
 'Broadside with 48 scenes illusrating  the misfortunes of a fat man',
 "Too fat, from 'News of the day,' published in Le Charivari, November 16, 1867",
 'Fat Courtesan with an Old Man and a Spectator in Costume, from 347 Suite',
 'The College Gate',
 'Novella del Grasso Legnaiuolo',
 'Standing boy',
 'Statuette of a fat boy (dwarf ?)',
 'Terracotta oil lamp',
 'Actors at the Hotel de Bourgogne',
 'A Sketch from Nature',
 'A Sketch from Nature',
 'Seated hollow figure with helmet',
 'Piece',
 'Candlestand (one of a pair)',
 'The Great Pyramid, Giza',
 'Sprite',
 'The Fat Boy (from Side Show)',
 'A seated fat lady',
 'Glass head-shaped flask',
 'Scenes from the Story of Joseph',
 'Marble portrait bust of a man',
 'George III pattern sovereign with St. George reverse',
 'George III pattern sovereign with St. George reverse',
 'King Henry IV',
 'The Ambassador of Good Will',
 'Figure-Celt Pendant',
 'Figure: Female (Akua Ba)',
 'Glass double head-shaped flask',
 'Statuette of Harpokrates',
 'Dance of Death in Seven Tempos (Dood - Dans in Zeven Tempos)',
 'Figure Vessel',
 'The Corsican Spider in His Web!',
 'The Corsican Spider in His Web!',
 'Four Caterpillars and a Snail',
 'The Fat Kitchen, from the series Monkeys',
 'Fat Free Surrealism, Curated by Red Grooms',
 'Dropsy Courting Consumption',
 'Dropsy Courting Consumption',
 'Sketchbook of Figure Studies',
 'no title',
 'Glass double head flask',
 'Funerary Mask',
 'Bird Pendant',
 'Two Female Nudes; Seated Male Nude (after Michelangelo?); Three Equestrian Figures (from Sketchbook)',
 'Wavy-handled jar',
 'Ground Zero',
 'Garbage is valuable',
 'The Holy Friar',
 '[Crowd Viewing "Fat Boy"]',
 'Fat Claude and her Girlfriend at Le Monocle',
 'This Hog the Property of Mr. William White of Kingston, Surrey...',
 'Satyrical Poetry',
 'Camp Lakecrest campers walking away, Dutchess County, N.Y.',
 'Girl with a plaid shirt at Camp Lakecrest, Dutchess County, N.Y.',
 'Vase Nº 2980',
 'Girl sitting in the grass at Camp Lakecrest, Dutchess County, N.Y.',
 'Girls standing in a line at Camp Lakecrest, Dutchess County, N.Y.',
 'Infant Bacchus with Grapes',
 'no title',
 'Staff with Snuff Vessels',
 'Dressing for a Masquerade',
 'Dressing for a Masquerade',
 'On Tue Le Veau Gras (One Kills The Fat Calf), from "L\'Enfant Prodigue" (The Prodigal Son)',
 'On Tue Le Veau Gras (One Kills The Fat Calf), from "L\'Enfant Prodigue" (The Prodigal Son)',
 "A fat british man in a wig, bound in L'Oeuvre original de Vivant Denon. Collection de eaux-fortes, Volume 2",
 'Costumed Figure',
 'Girl with a baseball glove at Camp Lakecrest, Dutchess County, N.Y.',
 'Transvestite with a torn stocking, N.Y.C.',
 'Engraved pearl shell',
 'Engraved pearl shell',
 'Engraved pearl shell',
 'Engraved pearl shell with human hair string',
 'Engraved pearl shell',
 'Engraved pearl shell',
 'Henry on roller skates pushed by a fat man\'s stomach, from the "Little Henry" (T78), issued with Tareyton Cigarettes by the R. J. Reynolds Tobacco Company',
 'Nobody Loves a Fat Man, from the "Mutt and Jeff" series (T88), issued with Sweet Caporal Cigarettes by Kinney Brothers Tobacco Company',
 'Nobody Loves A Fat Man, from the "Mutt and Jeff" series (T88), issued with Sweet Caporal Cigarettes by Kinney Brothers Tobacco Company',
 'Nobody Loves A Fat Man, from the "Mutt and Jeff" series (T88), issued with Sweet Caporal Cigarettes by Kinney Brothers Tobacco Company',
 'Prize Fat Cattle',
 'The Fat Cow Invaded..., from "Actualités"',
 'The Fat Kitchen',
 '[Alma Mahler Doll Made for Oskar Kokoschka by Hermine Moos]',
 'no title',
 'Female Fertility Figure (Akuaba)',
 'Dressing for a Birthday',
 'Dressing for a Birthday',
 '100 Woodcuts by Posada / 100 Grabados en madera por Posada',
 "Bull's Head Tavern",
 '[Five 35mm Film Frames: Subway Passengers, New York City: Two Men in Suits]',
 '[Five 35mm Film Frames: Subway Passengers, New York City: Two Men in Suits]',
 '[Five 35mm Film Frames: Subway Passengers, New York City: Two Men in Suits]',
 'Night-Shining White',
 'Design for a Frontispiece:  Mercury and Fame',
 'Engraved pearl shell and hair-string belt (riji, or jakoli, longkalongka)',
 'Frenchmen in November',
 'Nobody Loves A Fat Man, from the "Mutt and Jeff" series (T88), issued by Kinney Brothers Tobacco Company',
 'Nobody Loves A Fat Man, from the "Mutt and Jeff" series (T88),  issued with Sweet Caporal Cigarettes by Kinney Brothers Tobacco Company',
 'Nobody Loves A Fat Man, from the "Mutt and Jeff" series (T88),  issued with Sweet Caporal Cigarettes by Kinney Brothers Tobacco Company',
 'Openwork furniture plaque showing a cow suckling a calf',
 'Bust of a deformed man with a hat and a fat, protruding lower lip in profile to left',
 'New Years Greeting showing a table laden with food',
 'Itelmen Preparing Fish to be Dried',
 'Prayer book with case (mahdar)',
 'Headrest',
 'Pochette',
 'Madonna and Child with Saints Francis and Jerome',
 'Copped at a Cock Fight',
 'Cain fleeing after having slain Abel',
 'In and Out of Condition',
 'A Fair Start: "Take de water togedder when yous hear de shot!"',
 'Transvestite on a couch, N.Y.C.',
 'A Literary Debate in the Darktown Club: The Question Settled',
 'Returning Home',
 'Courtly Odes, Beginning with "Wild Geese"',
 'An Emaciated Horse Led by His Master',
 'From Soho',
 'From Eaton',
 'From Warwick Lane, from "Caricatures of the English"',
 'The Darktown Hook and Ladder Corps: In Action',
 'The "Bab" Ballads, Much Sound and Little Sense',
 'Marble tripod or altar found at Ostia by Gavin Hamilton in 1775, from "Vasi, candelabri, cippi, sarcofagi, tripodi, lucerne, ed ornamenti antichi disegnati ed incisi dal Cav. Gio. Batt. Piranesi, Vol. I" (Vases, candelabra, grave stones, sarcophagi, tripods, lamps, and ornaments designed and etched by Cavalieri Giovanni Battista Piranesi)',
 'Plan of the Baths of Diocletian..., tome 1, tavola 42 from "Le Antichità Romane" (Roman Antiquities)',
 'Eighteen Songs of a Nomad Flute: The Story of Lady Wenji',
 'Room found in 1758 among the ruins of an ancient villa on the Appian Way at Frattochie, near Albano, from which the ancient manner of heating and cooling rooms was discovered [sectional diagram], tavola 26 b from "Antichità d\'Albano e di Castel Gandolfo Descritte ed incise da Giovambatista Piranesi" (Antiquities of Albano and of Castel Gandolfo described and etched by Giovambattista Piranesi)',
 'Room found in 1758 among the ruins of an ancient villa on the Appian Way at Frattochie, near Albano, from which the ancient manner of heating and cooling rooms was discovered [sectional diagram], tavola 26 b from "Antichità d\'Albano e di Castel Gandolfo Descritte ed incise da Giovambatista Piranesi" (Antiquities of Albano and of Castel Gandolfo described and etched by Giovambattista Piranesi)',
 'Blue Monday',
 'Palazzo Pontificio (Palazzo Quirinale)',
 'The Darktown Fire Brigade -- Hook and Ladder Gymnastics: "Brace her up dar! and cotch her on de fly!"',
 'Redemption – Repudiation : Prosperity – Ruin',
 'no title',
 'September Morn',
 'Prayer Book: Arganonä Maryam (The Organ of Mary)',
 'Jack in Office']

# if 'title' : 'Jar Label ', 'Wig', 'Bowl', 'Candlestick' in METfw:
#     remove(item['title'])
#       else:
#       METfw.append(item)

# for item_to_remove in ['Label', 'Wig', 'Bowl of Fat', 'Candlestick', 'Engraved pearl shell']:
#   if item_to_remove in METfw:  # Check if the item exists before removing to avoid ValueError
#         METfw.remove(item_to_remove)

titles = [] # IDs, titles, descriptions, dates, nationality, medium/format, genders, and image links
names = []
genders = []
mediums = []
dates = []
countries = []
nationalities = []
image_urls = []
urls = []
departments = []

for item in results:
    title = item.get('title')
    titles.append(title)
    name = item.get('artistDisplayName')
    names.append(name)
    gender = item.get('artistGender')
    genders.append(gender)
    medium = item.get('medium')
    mediums.append(medium)
    date = item.get('objectDate')
    dates.append(date)
    country = item.get('country')
    countries.append(country)
    nationality = item.get('nationality')
    nationalities.append(nationality)
    image_url = item.get('primaryImage')
    image_urls.append(image_url)
    url = item.get('objectURL')
    urls.append(url)
    department = item.get('department')
    departments.append(department)

len(titles)

272

import pandas as pd
mdf = pd.DataFrame({
    'title': titles,
    'name': names,
    'medium': mediums,
    'date': dates,
    'country': countries,
    'image_url': image_urls,
    'objectURL': urls,
    'department': departments
})

mdf

mdf.to_csv('MET_fat_works.csv', index=False)

df1 = mdf.query("title in ['Jar Label','Wig','Bowl','Candlestick','Clay jar sealing','Jar Sealing','Fat Jar Label','Kohl Tube','Staff','Jar Label Type 140.1','Brush holder  in shape of bamboo','Ointment Jar','Kohl Container Decorated with Bes-images','Floral Garlands of Nauny','Club','Jar label fragment']")

df1

df2 = mdf.query("not (title in ['Hieratic Jar Label','Engraved pearl shell','Jar Label','Wig','Bowl','Bowl of Fat','Candlestick','Clay jar sealing','Jar Sealing','Fat Jar Label','Kohl Tube','Staff','Jar Label Type 140.1','Brush holder  in shape of bamboo','Ointment Jar','Kohl Container Decorated with Bes-images','Floral Garlands of Nauny','Club','Jar label fragment'])")

pd.set_option('display.max_rows', None)
df2

df2.info()

<class 'pandas.core.frame.DataFrame'>
Index: 197 entries, 4 to 271
Data columns (total 8 columns):
 #   Column      Non-Null Count  Dtype 
---  ------      --------------  ----- 
 0   title       193 non-null    object
 1   name        193 non-null    object
 2   medium      193 non-null    object
 3   date        193 non-null    object
 4   country     193 non-null    object
 5   image_url   193 non-null    object
 6   objectURL   193 non-null    object
 7   department  193 non-null    object
dtypes: object(8)
memory usage: 13.9+ KB

department = df2['department']

department.value_counts()

country = df2['country']

country.value_counts()

medium = df2['medium'] #needs to be cleaned to larger groups of mediums

pd.set_option('display.max_rows', None)
medium.value_counts()

date = df2['date']
date.value_counts() #Needs to be cleaned to have just the years or groups of years by decade, possible duplicates in the 1920's # https://stackoverflow.com/questions/39917568/how-to-modify-a-pandas-column-filled-text

# Replace all occurrences of 'apple' with 'grape' in column 'A'
#df['A'] = df['A'].replace('apple', 'grape')

date.describe()

df2.describe()

df2.to_csv('MET_fat_ART.csv', index=False)

import pandas as pd

df3 = pd.read_csv('MET_fat_ART_cleaned - MET_fat_ART (3).csv')

pd.set_option('display.max_rows', None)
df3

date = df3['date']
date.value_counts()

country = df3['country']
department = df3['department']
medium = df3['medium']
date = df3['date']

# DIDNT WORK df3['century'] = (df3['date'] / 100) + 1 # Assuming 'date' contains integer years
#     # Additional logic may be needed to handle B.C. dates or other date formats
# century = df3['century']

df3['medium'] = df3['medium'].str.replace('Lithograph, printed in color', 'Lithograph')
df3['medium'] = df3['medium'].str.replace('Hand-colored lithograph', 'Lithograph')
df3['medium'] = df3['medium'].str.replace('Lithograph on newsprint; second state of two (Delteil)', 'Lithograph')
df3['medium'] = df3['medium'].str.replace('Heavy card stock, lithography, watercolor, thread', 'Lithograph')
df3['medium'] = df3['medium'].str.replace('Lithograph printed in color with gum arabic', 'Lithograph')
df3['medium'] = df3['medium'].str.replace('Commercial lithograph', 'Lithograph')
df3['medium'] = df3['medium'].str.replace('Commercial color lithograph', 'Lithograph')
df3['medium'] = df3['medium'].str.replace('Hand-colored lithograph with gum arabic', 'Lithograph')
df3['medium'] = df3['medium'].str.replace('Lithograph printed in color', 'Lithograph')
df3['medium'] = df3['medium'].str.replace('Lithograph printed in color with gum arabic', 'Lithograph')
df3['medium'] = df3['medium'].str.replace('Commercial color lithograph reproducing drawing', 'Lithograph')
df3['medium'] = df3['medium'].str.replace('Lithograph and pen and brown ink on newsprint; third state of three, proof (Delteil)', 'Lithograph')
df3['medium'] = df3['medium'].str.replace('Lithograph reproducing drawing', 'Lithograph')
df3['medium'] = df3['medium'].str.replace('Lithograph printed in color with gum arabic', 'Lithograph')
df3['medium'] = df3['medium'].str.replace('Lithograph with gum arabic', 'Lithograph')
df3['medium'] = df3['medium'].str.replace('Hand-colored Lithograph', 'Lithograph')

df3['medium'] = df3['medium'].str.replace('Hand-colored etching and stipple, printed in brown ink', 'Etching')
df3['medium'] = df3['medium'].str.replace('Hand-colored etching and stipple', 'Etching')
df3['medium'] = df3['medium'].str.replace('Etching; only state', 'Etching')
df3['medium'] = df3['medium'].str.replace('Etching on blue paper', 'Etching')
df3['medium'] = df3['medium'].str.replace('Etching and stipple', 'Etching')
df3['medium'] = df3['medium'].str.replace('Etching; first state of three', 'Etching')
df3['medium'] = df3['medium'].str.replace('Etching; third state', 'Etching')
df3['medium'] = df3['medium'].str.replace('Etching; second state', 'Etching')
df3['medium'] = df3['medium'].str.replace('Etching; second state of three (Lieure)', 'Etching')
df3['medium'] = df3['medium'].str.replace('Etching and engraving', 'Etching')
df3['medium'] = df3['medium'].str.replace('Hand-colored etching and aquatint', 'Etching')
df3['medium'] = df3['medium'].str.replace('Etching; after third state', 'Etching')
df3['medium'] = df3['medium'].str.replace('Etching on laid paper; second state of two', 'Etching')
df3['medium'] = df3['medium'].str.replace('Etching, between second and third states', 'Etching')
df3['medium'] = df3['medium'].str.replace('Hand-colored etching', 'Etching')
df3['medium'] = df3['medium'].str.replace('Etching, printed in brown ink', 'Etching')
df3['medium'] = df3['medium'].str.replace('Etching of three (Lieure)', 'Etching')

df3['medium'] = df3['medium'].str.replace('Ceramic, cinnabar, red ochre', 'Ceramic')
df3['medium'] = df3['medium'].str.replace('Ceramic, pigment', 'Ceramic')
df3['medium'] = df3['medium'].str.replace('Ceramic, slip', 'Ceramic')
df3['medium'] = df3['medium'].str.replace('Glazed ceramic', 'Ceramic')

df3['medium'] = df3['medium'].str.replace('Bronze, gold', 'Bronze')
df3['medium'] = df3['medium'].str.replace('Bronze, ivory', 'Bronze')
df3['medium'] = df3['medium'].str.replace('Bronze, silver inlay (eyes), on a later porphyry and ormolu base', 'Bronze')

df3['medium'] = df3['medium'].str.replace('Engraving; first state', 'Engraving')
df3['medium'] = df3['medium'].str.replace('Engraving; first state of three', 'Engraving')

df3['medium'] = df3['medium'].str.replace('Handscroll; ink and color on silk', 'Handscroll; ink ')
df3['medium'] = df3['medium'].str.replace('Handscroll; ink on paper', 'Handscroll; ink ')
df3['medium'] = df3['medium'].str.replace('Handscroll; ink, color, and gold on silk', 'Handscroll; ink ')

df3['medium'] = df3['medium'].str.replace('Ink; on silk', 'Ink')
df3['medium'] = df3['medium'].str.replace('Ink, graphite, and crayon on heavy cream board/card', 'Ink')

df3['medium'] = df3['medium'].str.replace('Pen and black ink', 'Pen and Ink')
df3['medium'] = df3['medium'].str.replace('Pen and black ink, brush and gray wash, over black chalk', 'Pen and Ink')
df3['medium'] = df3['medium'].str.replace('Pen and black ink, gray wash', 'Pen and Ink')
df3['medium'] = df3['medium'].str.replace('Pen and brown ink with pen and black ink and brush and gray wash. Composition outlined in pen and brown ink. Contours incised and verso blackened with carbon dust for transfer', 'Pen and Ink')
df3['medium'] = df3['medium'].str.replace('Pen and ink on lined blue paper', 'Pen and Ink')
df3['medium'] = df3['medium'].str.replace('Pen, iron-gaul ink and graphite on off-white laid paper', 'Pen and Ink')
df3['medium'] = df3['medium'].str.replace('Pen and Ink, brush and gray wash, over black chalk', 'Pen and Ink')

df3['medium'] = df3['medium'].str.replace('Wood, beads, fiber', 'Wood')

print(df3['medium'])

0                                         Jade (jadeite)
1                                             Terracotta
2                                                 Marble
3                                                Jadeite
4                                                  Glass
5                                                  Glass
6                                                  Glass
7                                                Ceramic
8                                                Ceramic
9                                                Ceramic
10                                      Handscroll; ink 
11                                      Handscroll; ink 
12                                      Handscroll; ink 
13     High-copper alloy, fire-gilt, brown natural pa...
14                                                Bronze
15                                       Tempera on wood
16                                             Engraving
17                                                 Ivory
18                                                   NaN
19                                             Engraving
20                                    Engraving of three
21                                             Engraving
22                                               Etching
23                                               Etching
24                                               Etching
25                                               Etching
26                                               Etching
27                                               Etching
28                                           Pen and Ink
29          Parchment, pigment ink, wood, leather, fiber
30                                               Etching
31                                               Etching
32                                               Etching
33                           Ink and watercolor on paper
34        Album of twelve leaves; ink and color on paper
35                                                 Ivory
36                                Oil and gold on copper
37                                         Oil on canvas
38                                               Etching
39                                               Etching
40                                               Etching
41                                Pen and Ink, gray wash
42                                Pen and Ink, gray wash
43     Pair of six-panel folding screens; ink and col...
44                                               Etching
45                                               Etching
46                                           Pen and Ink
47     Oak veneered with tulipwood, amaranth, holly, ...
48                                               Etching
49                                               Etching
50                                               Etching
51                                               Etching
52                                               Etching
53     Carved and painted basswood, glass and gilded-...
54                                               Etching
55                                               Etching
56                                 Etching; second state
57                                               Etching
58                                               Etching
59                                               Etching
60                                               Etching
61                                               Etching
62                                               Etching
63                                                  Wood
64                                                  Wood
65     Parchment (vellum), pigment (red, blue, ochre,...
66                    Brush and gray wash, over graphite
67                                               Etching
68                                               Etching
69                                               Etching
70                                               Etching
71                                               Etching
72                                               Etching
73                                               Etching
74                                               Etching
75                                               Etching
76                                            Lithograph
77     Cardboard (cover)\nDrawings in ink, wash, and ...
78                                           Pen and Ink
79                                                  Gold
80                                                  Gold
81                                            Lithograph
82                                    Terracotta; marble
83                                               Etching
84                                         Oil on canvas
85                                                Cotton
86                                                  Wood
87                                                  Wood
88                                            Lithograph
89                                            Lithograph
90                                           Pen and Ink
91                                        Wood engraving
92                                    Lithograph and Ink
93                                         Color process
94                                    Oil on slate paper
95                                Illustrations: woodcut
96                                            Lithograph
97                                                   Ink
98                                            Lithograph
99                                            Lithograph
100                                           Lithograph
101                                           Lithograph
102                                              Etching
103                                           Lithograph
104                                           Lithograph
105                                           Lithograph
106                                           Lithograph
107                                           Lithograph
108                       Pearl shell, human hair, ocher
109                                  Wood, beads, string
110                                        Oil on canvas
111                                           Lithograph
112                                           Lithograph
113                                           Lithograph
114                                           Lithograph
115                                           Lithograph
116                                           Lithograph
117                                        Oil on canvas
118                                           Lithograph
119                                 Gelatin silver print
120                                           Lithograph
121                                           Lithograph
122                                           Lithograph
123                                           Lithograph
124                                           Lithograph
125                                           Lithograph
126                                           Lithograph
127                                           Lithograph
128                                           Lithograph
129                                           Lithograph
130                                           Lithograph
131                                           Lithograph
132    Frieze of seven woodcuts plus title printed on...
133                                 Gelatin silver print
134                                           Lithograph
135                                        Film negative
136                                        Film negative
137                                        Film negative
138    Carved Australian Gold-Lipped Pearl Shell, Pin...
139                                        Oil on canvas
140                                              Woodcut
141                                 Gelatin silver print
142                                          Pen and Ink
143                                 Gelatin silver print
144                                 Gelatin silver print
145                                 Gelatin silver print
146                                 Gelatin silver print
147                                              Etching
148                                              Etching
149                                              Etching
150                                              Etching
151                                  Sugar lift aquatint
152                                 Gelatin silver print
153                                 Gelatin silver print
154                                 Gelatin silver print
155                                 Gelatin silver print
156                                 Gelatin silver print
157                       Wood engraving; working proofs
158            Mahogany, maple, rosewood, metal, plastic
159                                               Bronze
160    Gouache, tempera, and cut, torn, and pasted pa...
161                         Photomechanical reproduction
162                                              Ceramic
163                                              Ceramic
164                                            Limestone
165                                            Limestone
166                                      Pottery and ink
167                            Paper, tempera paint, ink
168    Cartonnage, gold, travertine (Egyptian alabast...
169                 Fine-grained grey stone (graywacke?)
170                                              Granite
171                    Plastered and painted wood, gesso
172                                                 Gold
173                                            Limestone
174                                              Ceramic
175                                              Pottery
176                                               Bronze
177                                       Cupreous metal
178        Limestone, organic material, paint, malachite
179                                            Greywacke
180                                           Terracotta
181                                           Terracotta
182                                               Bronze
183                                              Ceramic
184                                       Cupreous metal
185                                       Cupreous metal
186                                                Ivory
187                                               Bronze
188                                              Etching
189                                              Etching
Name: medium, dtype: object

med = df3['medium']

df3

med.value_counts()

df3.value_counts('medium').nlargest(15).plot(kind='barh', xlabel='Number of Fat', ylabel='Art Medium', title='Most Frequent Mediums used to Represent Fatness')

<Axes: title={'center': 'Most Frequent Mediums used to Represent Fatness'}, xlabel='Number of Fat', ylabel='Art Medium'>

df3.value_counts('date').nlargest(20).plot(kind='barh', xlabel='Frequency', ylabel='Years', title='Years with the Most Fat Artwork')

<Axes: title={'center': 'Years with the Most Fat Artwork'}, xlabel='Frequency', ylabel='Years'>

df3.value_counts('date').nlargest(40).plot(kind='barh') # create intervals by every 50 / 100 years.

<Axes: ylabel='date'>

date.describe()

df3.value_counts('department').plot(kind='barh',xlabel='Frequency', ylabel='Departments in the MET', title='Number of Fat Artworks in Each Department')
#fig = data.value_counts('column').plot(kind='barh').get_figure
#fig.savefig('filename.png', bbox_inches='tight)

<Axes: title={'center': 'Number of Fat Artworks in Each Department'}, xlabel='Frequency', ylabel='Departments in the MET'>

# cent_1 = df3['date'].str.contains('1 - 74', na=False) # Didn't work
# cent_3 = df3['date'].str.contains('2', na=False)
# cent_4 = df3['date'].str.contains('3', na=False)
# cent_7 = df3['date'].str.contains('6', na=False)
# cent_8 = df3['date'].str.contains('7', na=False)
# cent_12 = df3['date'].str.contains('11', na=False)
# cent_15 = df3['date'].str.contains('14', na=False) #how to exclude BCE
# cent_16 = df3['date'].str.contains('15', na=False) #how to exclude BCE
# cent_17 = df3['date'].str.contains('16', na=False) #how to exclude BCE
# cent_18 = df3['date'].str.contains('17', na=False) #how to exclude BCE
# cent_19 = df3['date'].str.contains('18', na=False)
# cent_20 = df3['date'].str.contains('19', na=False)

# BCE = df3['date'].str.contains('BCE', na=False)

# cent_1 = df3['date'].str.contains('1', na=False) & ~df3['date'].str.contains('BCE', na=False)
# | (df3['date'].str.contains('74', na=False)
# Didn't work
# Tried this formulas to group dates by century

df3['date'][19]

1563.0

# df3['date'] = pd.to_datetime(df3['date'], format='%Y')
# df3['date'] = pd.to_numeric(df3['date'], errors='coerce')

BCE = df3[df3['date'].isin(range(-3381, 0))]
cent_1 = df3[df3['date'].isin([1, 74])]
cent_3 = df3[df3['date'].isin(range(200,299))]
cent_4 = df3[df3['date'].isin(range(300,399))]
cent_7 = df3[df3['date'].isin(range(600,699))]
cent_8 = df3[df3['date'].isin(range(700,799))]
cent_12 = df3[df3['date'].isin(range(1100,1199))]
cent_15 = df3[df3['date'].isin(range(1400,1499))]
cent_16 = df3[df3['date'].isin(range(1500,1599))]
cent_17 = df3[df3['date'].isin(range(1600,1699))]
cent_18 = df3[df3['date'].isin(range(1700,1799))]
cent_19 = df3[df3['date'].isin(range(1800,1899))]
cent_20 = df3[df3['date'].isin(range(1900,1999))]
cent_21 = df3[df3['date'].isin(range(2000,2099))]

# | (df3['date'] == '74')]
# & (df3['date'] != 'BCE')]

display(BCE)

cent_1

cent_1['medium'].value_counts()

# _20th_century = df3[cent_20]
# _19th_century = df3[cent_19]
# _18th_century = df3[cent_18]
# _17th_century = df3[cent_17]
# _16th_century = df3[cent_16]
# _15th_century = df3[cent_15]
# _12th_century = df3[cent_12]
# _8th_century = df3[cent_8]
# _7th_century = df3[cent_7]
# _3rd_century = df3[cent_3]
# _1st_century = df3[cent_1]

# ancient_art['medium'].value_counts()

#_20th_century['medium'].value_counts()

---------------------------------------------------------------------------
NameError                                 Traceback (most recent call last)
<ipython-input-24-daa9a9540387> in <cell line: 1>()
----> 1 _20th_century['medium'].value_counts()

NameError: name '_20th_century' is not defined

#create data frame for each century and then make a new df with the highest medium for each century

# how to combine into a new DF combined_df = pd.concat([BCE, cent_1, cent_3, cent_4, cent_7, cent_8, cent_12, cent_15, cent_16, cent_17, cent_18, cent_19, cent_20])

BCE_max = BCE['medium'].value_counts().idxmax()
cent_1_max = cent_1['medium'].value_counts().idxmax()
cent_3_max = cent_3['medium'].value_counts().idxmax()
cent_4_max = cent_4['medium'].value_counts().idxmax()
cent_7_max = cent_7['medium'].value_counts().idxmax()
cent_8_max = cent_8['medium'].value_counts().idxmax()
cent_12_max = cent_12['medium'].value_counts().idxmax()
cent_15_max = cent_15['medium'].value_counts().idxmax()
cent_16_max = cent_16['medium'].value_counts().idxmax()
cent_17_max = cent_17['medium'].value_counts().idxmax()
cent_18_max = cent_18['medium'].value_counts().idxmax()
cent_19_max = cent_19['medium'].value_counts().idxmax()
cent_20_max = cent_20['medium'].value_counts().idxmax()
cent_21_max = cent_21['medium'].value_counts().idxmax()

# value_counts() produces name of medium no numbers, can add in later using Freq

BCE_max

'Ceramic'

import pandas as pd


# Create a dictionary to store the most frequent medium for each century
max_mediums = {
    "BCE": BCE['medium'].value_counts().idxmax(),
    "1st Century": cent_1['medium'].value_counts().idxmax(),
    "3rd Century": cent_3['medium'].value_counts().idxmax(),
    "4th Century": cent_4['medium'].value_counts().idxmax(),
    "7th Century": cent_7['medium'].value_counts().idxmax(),
    "8th Century": cent_8['medium'].value_counts().idxmax(),
    "12th Century": cent_12['medium'].value_counts().idxmax(),
    "15th Century": cent_15['medium'].value_counts().idxmax(),
    "16th Century": cent_16['medium'].value_counts().idxmax(),
    "17th Century": cent_17['medium'].value_counts().idxmax(),
    "18th Century": cent_18['medium'].value_counts().idxmax(),
    "19th Century": cent_19['medium'].value_counts().idxmax(),
    "20th Century": cent_20['medium'].value_counts().idxmax(),
    "21st Century": cent_21['medium'].value_counts().idxmax()
}
Freq = {  # Define the Freq dictionary here
    "BCE": BCE['medium'].value_counts().max(),
    "1st Century": cent_1['medium'].value_counts().max(),
    "3rd Century": cent_3['medium'].value_counts().max(),
    "4th Century": cent_4['medium'].value_counts().max(),
    "7th Century": cent_7['medium'].value_counts().max(),
    "8th Century": cent_8['medium'].value_counts().max(),
    "12th Century": cent_12['medium'].value_counts().max(),
    "15th Century": cent_15['medium'].value_counts().max(),
    "16th Century": cent_16['medium'].value_counts().max(),
    "17th Century": cent_17['medium'].value_counts().max(),
    "18th Century": cent_18['medium'].value_counts().max(),
    "19th Century": cent_19['medium'].value_counts().max(),
    "20th Century": cent_20['medium'].value_counts().max(),
    "21st Century": cent_21['medium'].value_counts().max()
}
# Create a DataFrame from the dictionary
data = []
for century in max_mediums:
    data.append({
        'Century': century,
        'Most Frequent Medium': max_mediums[century],
        'Freq': Freq[century]  # Access frequency from the Freq dictionary
    })

# Create a DataFrame from the list of dictionaries
max_df = pd.DataFrame(data)

max_df

from matplotlib import pyplot as plt
import seaborn as sns  # seaborn for prettier graphs <3
max_df.groupby('Most Frequent Medium').size().plot(kind='barh', xlabel='Number of Centuries', ylabel='Art Mediums', title='Most Frequent Medium Representing Fatness Over the Centuries', color=sns.palettes.mpl_palette('Dark2'))
plt.gca().spines[['top', 'right']].set_visible(False)

BCE.value_counts('medium').nlargest(20).plot(kind='barh', xlabel='Number of Artworks', ylabel='Mediums', title='Most Frequent Mediums used to Represent Fatness in Artwork made BCE')

<Axes: title={'center': 'Most Frequent Mediums used to Represent Fatness in Artwork made BCE'}, xlabel='Number of Artworks', ylabel='Mediums'>

BCE.value_counts('medium')

cent_1.value_counts('medium').nlargest(10).plot(kind='barh', xlabel='Number of Artworks', ylabel='Mediums', title='Most Frequent Mediums used to Represent Fatness in Artwork made in the 1st Century')

<Axes: title={'center': 'Most Frequent Mediums used to Represent Fatness in Artwork made in the 1st Century'}, xlabel='Number of Artworks', ylabel='Mediums'>

cent_1.value_counts('medium')

cent_3.value_counts('medium').nlargest(20).plot(kind='barh', xlabel='Number of Artworks', ylabel='Mediums', title='Most Frequent Mediums used to Represent Fatness in Artwork made in the 3rd Century')

<Axes: title={'center': 'Most Frequent Mediums used to Represent Fatness in Artwork made in the 3rd Century'}, xlabel='Number of Artworks', ylabel='Mediums'>

cent_3.value_counts('medium')

cent_4.value_counts('medium').nlargest(20).plot(kind='barh', xlabel='Number of Artworks', ylabel='Mediums', title='Most Frequent Mediums used to Represent Fatness in Artwork made in the 4th Century')

<Axes: title={'center': 'Most Frequent Mediums used to Represent Fatness in Artwork made in the 4th Century'}, xlabel='Number of Artworks', ylabel='Mediums'>

cent_7.value_counts('medium').nlargest(20).plot(kind='barh', xlabel='Number of Artworks', ylabel='Mediums', title='Most Frequent Mediums used to Represent Fatness in Artwork made in the 7th Century')

<Axes: title={'center': 'Most Frequent Mediums used to Represent Fatness in Artwork made in the 7th Century'}, xlabel='Number of Artworks', ylabel='Mediums'>

cent_8.value_counts('medium').nlargest(20).plot(kind='barh', xlabel='Number of Artworks', ylabel='Mediums', title='Most Frequent Mediums used to Represent Fatness in Artwork made in the 8th Century')

<Axes: title={'center': 'Most Frequent Mediums used to Represent Fatness in Artwork made in the 8th Century'}, xlabel='Number of Artworks', ylabel='Mediums'>

cent_12.value_counts('medium').nlargest(20).plot(kind='barh', xlabel='Number of Artworks', ylabel='Mediums', title='Most Frequent Mediums used to Represent Fatness in Artwork made in the 12th Century')

<Axes: title={'center': 'Most Frequent Mediums used to Represent Fatness in Artwork made in the 12th Century'}, xlabel='Number of Artworks', ylabel='Mediums'>

cent_15.value_counts('medium').nlargest(20).plot(kind='barh', xlabel='Number of Artworks', ylabel='Mediums', title='Most Frequent Mediums used to Represent Fatness in Artwork made in the 15th Century')

<Axes: title={'center': 'Most Frequent Mediums used to Represent Fatness in Artwork made in the 15th Century'}, xlabel='Number of Artworks', ylabel='Mediums'>

cent_16.value_counts('medium').nlargest(20).plot(kind='barh', xlabel='Number of Artworks', ylabel='Mediums', title='Most Frequent Mediums used to Represent Fatness in Artwork made in the 16th Century')

<Axes: title={'center': 'Most Frequent Mediums used to Represent Fatness in Artwork made in the 16th Century'}, xlabel='Number of Artworks', ylabel='Mediums'>

cent_17.value_counts('medium').nlargest(20).plot(kind='barh', xlabel='Number of Artworks', ylabel='Mediums', title='Most Frequent Mediums used to Represent Fatness in Artwork made in the 17th Century')

<Axes: title={'center': 'Most Frequent Mediums used to Represent Fatness in Artwork made in the 17th Century'}, xlabel='Number of Artworks', ylabel='Mediums'>

cent_18.value_counts('medium').nlargest(20).plot(kind='barh', xlabel='Number of Artworks', ylabel='Mediums', title='Most Frequent Mediums used to Represent Fatness in Artwork made in the 18th Century')

<Axes: title={'center': 'Most Frequent Mediums used to Represent Fatness in Artwork made in the 18th Century'}, xlabel='Number of Artworks', ylabel='Mediums'>

cent_19.value_counts('medium').nlargest(20).plot(kind='barh', xlabel='Number of Artworks', ylabel='Mediums', title='20 Most Frequent Mediums used to Represent Fatness in Artwork made in the 19th Century')

<Axes: title={'center': '20 Most Frequent Mediums used to Represent Fatness in Artwork made in the 19th Century'}, xlabel='Number of Artworks', ylabel='Mediums'>

cent_20.value_counts('medium').nlargest(20).plot(kind='barh', xlabel='Number of Artworks', ylabel='Mediums', title='Most Frequent Mediums used to Represent Fatness in Artwork made in the 20th Century')

<Axes: title={'center': 'Most Frequent Mediums used to Represent Fatness in Artwork made in the 20th Century'}, xlabel='Number of Artworks', ylabel='Mediums'>

pd.set_option('display.max_rows', None)
print(BCE['image_url'])

163    https://images.metmuseum.org/CRDImages/ao/orig...
164    https://images.metmuseum.org/CRDImages/eg/orig...
165    https://images.metmuseum.org/CRDImages/eg/orig...
166                                                  NaN
167    https://images.metmuseum.org/CRDImages/eg/orig...
168    https://images.metmuseum.org/CRDImages/eg/orig...
169    https://images.metmuseum.org/CRDImages/eg/orig...
170    https://images.metmuseum.org/CRDImages/eg/orig...
171    https://images.metmuseum.org/CRDImages/eg/orig...
172    https://images.metmuseum.org/CRDImages/ao/orig...
173    https://images.metmuseum.org/CRDImages/eg/orig...
174    https://images.metmuseum.org/CRDImages/ao/orig...
175    https://images.metmuseum.org/CRDImages/eg/orig...
176    https://images.metmuseum.org/CRDImages/gr/orig...
177    https://images.metmuseum.org/CRDImages/eg/orig...
178                                                  NaN
179    https://images.metmuseum.org/CRDImages/eg/orig...
180                                                  NaN
181    https://images.metmuseum.org/CRDImages/gr/orig...
182    https://images.metmuseum.org/CRDImages/gr/orig...
183    https://images.metmuseum.org/CRDImages/ao/orig...
184    https://images.metmuseum.org/CRDImages/eg/orig...
185    https://images.metmuseum.org/CRDImages/eg/orig...
186    https://images.metmuseum.org/CRDImages/an/orig...
187    https://images.metmuseum.org/CRDImages/gr/orig...
Name: image_url, dtype: object

BCE['objectURL'][178]
BCE['image_url'][178] = ['https://collectionapi.metmuseum.org/api/collection/v1/iiif/547202/1218864/main-image']

<ipython-input-35-b060eca9c26c>:2: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0!
You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy.
A typical example is when you are setting values in a column of a DataFrame, like:

df["col"][row_indexer] = value

Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`.

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy

  BCE['image_url'][178] = ['https://collectionapi.metmuseum.org/api/collection/v1/iiif/547202/1218864/main-image']
<ipython-input-35-b060eca9c26c>:2: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  BCE['image_url'][178] = ['https://collectionapi.metmuseum.org/api/collection/v1/iiif/547202/1218864/main-image']

BCE['objectURL'][180]

'https://www.metmuseum.org/art/collection/search/256170'

print(cent_7['objectURL'])

9    https://www.metmuseum.org/art/collection/searc...
Name: objectURL, dtype: object

BCE_URL = BCE['image_url'].to_list()
cent_1_URL = cent_1['image_url'].to_list()
cent_3_URL = cent_3['image_url'].to_list()
cent_4_URL = cent_4['image_url'].to_list()
#cent_7_URL = cent_7['image_url'].to_list() NOT AVAILABLE
cent_8_URL = cent_8['image_url'].to_list()
cent_12_URL = cent_12['image_url'].to_list()
cent_15_URL = cent_15['image_url'].to_list()
cent_16_URL = cent_16['image_url'].to_list()
cent_17_URL = cent_17['image_url'].to_list()
cent_18_URL = cent_18['image_url'].to_list()
cent_19_URL = cent_19['image_url'].to_list()
cent_20_URL = cent_20['image_url'].to_list()
cent_21_URL = cent_21['image_url'].to_list()

Link_list = BCE_URL + cent_1_URL + cent_3_URL + cent_4_URL + cent_8_URL + cent_12_URL + cent_15_URL + cent_16_URL + cent_17_URL + cent_18_URL + cent_19_URL + cent_20_URL + cent_21_URL

import matplotlib.pyplot as plt
import requests
from PIL import Image
from io import BytesIO

def plot_images_from_urls(url_list):
    fig, axes = plt.subplots(nrows=len(url_list), ncols=1, figsize=(5, 5 * len(url_list)))

    for i, url in enumerate(url_list):
        try:
            response = requests.get(url)
            response.raise_for_status()  # Raise exception for bad status codes
            img = Image.open(BytesIO(response.content))
            axes[i].imshow(img)
            axes[i].axis('off')  # Hide axis ticks and labels
        except Exception as e:
            print(f"Error loading image from {url}: {e}")

    plt.tight_layout()
    plt.show()
    plt.savefig('1.png', bbox_inches='tight')


url_list = cent_1_URL #intercgnage the URL list to the century list of URLS
plot_images_from_urls(url_list)

<Figure size 640x480 with 0 Axes>

import matplotlib.pyplot as plt
import requests
from PIL import Image
from io import BytesIO

def plot_images_from_urls(url_list):
    fig, axes = plt.subplots(nrows=len(url_list), ncols=1, figsize=(5, 5 * len(url_list)))

    for i, url in enumerate(url_list):
        try:
            response = requests.get(url)
            response.raise_for_status()  # Raise exception for bad status codes
            img = Image.open(BytesIO(response.content))
            axes[i].imshow(img)
            axes[i].axis('off')  # Hide axis ticks and labels
        except Exception as e:
            print(f"Error loading image from {url}: {e}")

    plt.tight_layout()
    plt.show()


url_list = cent_3_URL #intercgnage the URL list to the century list of URLS
plot_images_from_urls(url_list)

import matplotlib.pyplot as plt
import requests
from PIL import Image
from io import BytesIO

def plot_images_from_urls(url_list):
    fig, axes = plt.subplots(nrows=len(url_list), ncols=1, figsize=(5, 5 * len(url_list)))

    for i, url in enumerate(url_list):
        try:
            response = requests.get(url)
            response.raise_for_status()  # Raise exception for bad status codes
            img = Image.open(BytesIO(response.content))
            axes[i].imshow(img)
            axes[i].axis('off')  # Hide axis ticks and labels
        except Exception as e:
            print(f"Error loading image from {url}: {e}")

    plt.tight_layout()
    plt.show()


url_list = cent_4_URL #intercgnage the URL list to the century list of URLS
plot_images_from_urls(url_list)

#images for 7th century are nto available

import matplotlib.pyplot as plt
import requests
from PIL import Image
from io import BytesIO

def plot_images_from_urls(url_list):
    fig, axes = plt.subplots(nrows=len(url_list), ncols=1, figsize=(5, 5 * len(url_list)))

    for i, url in enumerate(url_list):
        try:
            response = requests.get(url)
            response.raise_for_status()  # Raise exception for bad status codes
            img = Image.open(BytesIO(response.content))
            axes[i].imshow(img)
            axes[i].axis('off')  # Hide axis ticks and labels
        except Exception as e:
            print(f"Error loading image from {url}: {e}")

    plt.tight_layout()
    plt.show()


url_list = cent_7_URL #intercgnage the URL list to the century list of URLS
plot_images_from_urls(url_list)

---------------------------------------------------------------------------
NameError                                 Traceback (most recent call last)
<ipython-input-82-16ce50b23831> in <cell line: 23>()
     21 
     22 
---> 23 url_list = cent_7_URL #intercgnage the URL list to the century list of URLS
     24 plot_images_from_urls(url_list)

NameError: name 'cent_7_URL' is not defined

import matplotlib.pyplot as plt
import requests
from PIL import Image
from io import BytesIO

def plot_images_from_urls(url_list):
    fig, axes = plt.subplots(nrows=len(url_list), ncols=1, figsize=(5, 5 * len(url_list)))

    for i, url in enumerate(url_list):
        try:
            response = requests.get(url)
            response.raise_for_status()  # Raise exception for bad status codes
            img = Image.open(BytesIO(response.content))
            axes[i].imshow(img)
            axes[i].axis('off')  # Hide axis ticks and labels
        except Exception as e:
            print(f"Error loading image from {url}: {e}")

    plt.tight_layout()
    plt.show()


url_list = cent_8_URL #intercgnage the URL list to the century list of URLS
plot_images_from_urls(url_list)

Error loading image from https://images.metmuseum.org/CRDImages/as/original/DP153705.jpg: 'Axes' object is not subscriptable

import matplotlib.pyplot as plt
import requests
from PIL import Image
from io import BytesIO

def plot_images_from_urls(url_list):
    fig, axes = plt.subplots(nrows=len(url_list), ncols=1, figsize=(5, 5 * len(url_list)))

    for i, url in enumerate(url_list):
        try:
            response = requests.get(url)
            response.raise_for_status()  # Raise exception for bad status codes
            img = Image.open(BytesIO(response.content))
            axes[i].imshow(img)
            axes[i].axis('off')  # Hide axis ticks and labels
        except Exception as e:
            print(f"Error loading image from {url}: {e}")

    plt.tight_layout()
    plt.show()


url_list = cent_12_URL #intercgnage the URL list to the century list of URLS
plot_images_from_urls(url_list)

Error loading image from https://images.metmuseum.org/CRDImages/as/original/DP147758_CRD.jpg: 'Axes' object is not subscriptable

import matplotlib.pyplot as plt
import requests
from PIL import Image
from io import BytesIO

def plot_images_from_urls(url_list):
    fig, axes = plt.subplots(nrows=len(url_list), ncols=1, figsize=(5, 5 * len(url_list)))

    for i, url in enumerate(url_list):
        try:
            response = requests.get(url)
            response.raise_for_status()  # Raise exception for bad status codes
            img = Image.open(BytesIO(response.content))
            axes[i].imshow(img)
            axes[i].axis('off')  # Hide axis ticks and labels
        except Exception as e:
            print(f"Error loading image from {url}: {e}")

    plt.tight_layout()
    plt.show()


url_list = cent_15_URL #intercgnage the URL list to the century list of URLS
plot_images_from_urls(url_list)

import matplotlib.pyplot as plt
import requests
from PIL import Image
from io import BytesIO

def plot_images_from_urls(url_list):
    fig, axes = plt.subplots(nrows=len(url_list), ncols=1, figsize=(5, 5 * len(url_list)))

    for i, url in enumerate(url_list):
        try:
            response = requests.get(url)
            response.raise_for_status()  # Raise exception for bad status codes
            img = Image.open(BytesIO(response.content))
            axes[i].imshow(img)
            axes[i].axis('off')  # Hide axis ticks and labels
        except Exception as e:
            print(f"Error loading image from {url}: {e}")

    plt.tight_layout()
    plt.show()


url_list = cent_16_URL #intercgnage the URL list to the century list of URLS
plot_images_from_urls(url_list)

Output hidden; open in https://colab.research.google.com to view.

import matplotlib.pyplot as plt
import requests
from PIL import Image
from io import BytesIO

def plot_images_from_urls(url_list):
    fig, axes = plt.subplots(nrows=len(url_list), ncols=1, figsize=(5, 5 * len(url_list)))

    for i, url in enumerate(url_list):
        try:
            response = requests.get(url)
            response.raise_for_status()  # Raise exception for bad status codes
            img = Image.open(BytesIO(response.content))
            axes[i].imshow(img)
            axes[i].axis('off')  # Hide axis ticks and labels
        except Exception as e:
            print(f"Error loading image from {url}: {e}")

    plt.tight_layout()
    plt.show()


url_list = cent_17_URL #intercgnage the URL list to the century list of URLS
plot_images_from_urls(url_list)

Output hidden; open in https://colab.research.google.com to view.

import matplotlib.pyplot as plt
import requests
from PIL import Image
from io import BytesIO

def plot_images_from_urls(url_list):
    fig, axes = plt.subplots(nrows=len(url_list), ncols=1, figsize=(5, 5 * len(url_list)))

    for i, url in enumerate(url_list):
        try:
            response = requests.get(url)
            response.raise_for_status()  # Raise exception for bad status codes
            img = Image.open(BytesIO(response.content))
            axes[i].imshow(img)
            axes[i].axis('off')  # Hide axis ticks and labels
        except Exception as e:
            print(f"Error loading image from {url}: {e}")

    plt.tight_layout()
    plt.show()


url_list = cent_18_URL #intercgnage the URL list to the century list of URLS
plot_images_from_urls(url_list)

Output hidden; open in https://colab.research.google.com to view.

import matplotlib.pyplot as plt
import requests
from PIL import Image
from io import BytesIO

def plot_images_from_urls(url_list):
    fig, axes = plt.subplots(nrows=len(url_list), ncols=1, figsize=(5, 5 * len(url_list)))

    for i, url in enumerate(url_list):
        try:
            response = requests.get(url)
            response.raise_for_status()  # Raise exception for bad status codes
            img = Image.open(BytesIO(response.content))
            axes[i].imshow(img)
            axes[i].axis('off')  # Hide axis ticks and labels
        except Exception as e:
            print(f"Error loading image from {url}: {e}")

    plt.tight_layout()
    plt.show()


url_list = cent_19_URL #intercgnage the URL list to the century list of URLS
plot_images_from_urls(url_list)

Output hidden; open in https://colab.research.google.com to view.

import matplotlib.pyplot as plt
import requests
from PIL import Image
from io import BytesIO

def plot_images_from_urls(url_list):
    fig, axes = plt.subplots(nrows=len(url_list), ncols=1, figsize=(5, 5 * len(url_list)))

    for i, url in enumerate(url_list):
        try:
            response = requests.get(url)
            response.raise_for_status()  # Raise exception for bad status codes
            img = Image.open(BytesIO(response.content))
            axes[i].imshow(img)
            axes[i].axis('off')  # Hide axis ticks and labels
        except Exception as e:
            print(f"Error loading image from {url}: {e}")

    plt.tight_layout()
    plt.show()


url_list = cent_20_URL #intercgnage the URL list to the century list of URLS
plot_images_from_urls(url_list)

Error loading image from nan: Invalid URL 'nan': No scheme supplied. Perhaps you meant https://nan?
Error loading image from nan: Invalid URL 'nan': No scheme supplied. Perhaps you meant https://nan?
Error loading image from nan: Invalid URL 'nan': No scheme supplied. Perhaps you meant https://nan?
Error loading image from nan: Invalid URL 'nan': No scheme supplied. Perhaps you meant https://nan?
Error loading image from nan: Invalid URL 'nan': No scheme supplied. Perhaps you meant https://nan?
Error loading image from nan: Invalid URL 'nan': No scheme supplied. Perhaps you meant https://nan?
Error loading image from nan: Invalid URL 'nan': No scheme supplied. Perhaps you meant https://nan?
Error loading image from nan: Invalid URL 'nan': No scheme supplied. Perhaps you meant https://nan?
Error loading image from nan: Invalid URL 'nan': No scheme supplied. Perhaps you meant https://nan?
Error loading image from nan: Invalid URL 'nan': No scheme supplied. Perhaps you meant https://nan?
Error loading image from nan: Invalid URL 'nan': No scheme supplied. Perhaps you meant https://nan?
Error loading image from nan: Invalid URL 'nan': No scheme supplied. Perhaps you meant https://nan?
Error loading image from nan: Invalid URL 'nan': No scheme supplied. Perhaps you meant https://nan?
Error loading image from nan: Invalid URL 'nan': No scheme supplied. Perhaps you meant https://nan?
Error loading image from nan: Invalid URL 'nan': No scheme supplied. Perhaps you meant https://nan?
Error loading image from nan: Invalid URL 'nan': No scheme supplied. Perhaps you meant https://nan?
Error loading image from nan: Invalid URL 'nan': No scheme supplied. Perhaps you meant https://nan?
Error loading image from nan: Invalid URL 'nan': No scheme supplied. Perhaps you meant https://nan?
Error loading image from nan: Invalid URL 'nan': No scheme supplied. Perhaps you meant https://nan?
Error loading image from nan: Invalid URL 'nan': No scheme supplied. Perhaps you meant https://nan?
Error loading image from nan: Invalid URL 'nan': No scheme supplied. Perhaps you meant https://nan?
Error loading image from nan: Invalid URL 'nan': No scheme supplied. Perhaps you meant https://nan?
Error loading image from nan: Invalid URL 'nan': No scheme supplied. Perhaps you meant https://nan?
Error loading image from nan: Invalid URL 'nan': No scheme supplied. Perhaps you meant https://nan?
Error loading image from nan: Invalid URL 'nan': No scheme supplied. Perhaps you meant https://nan?
Error loading image from nan: Invalid URL 'nan': No scheme supplied. Perhaps you meant https://nan?
Error loading image from nan: Invalid URL 'nan': No scheme supplied. Perhaps you meant https://nan?
Error loading image from nan: Invalid URL 'nan': No scheme supplied. Perhaps you meant https://nan?
Error loading image from nan: Invalid URL 'nan': No scheme supplied. Perhaps you meant https://nan?
Error loading image from nan: Invalid URL 'nan': No scheme supplied. Perhaps you meant https://nan?
Error loading image from nan: Invalid URL 'nan': No scheme supplied. Perhaps you meant https://nan?
Error loading image from nan: Invalid URL 'nan': No scheme supplied. Perhaps you meant https://nan?
Error loading image from nan: Invalid URL 'nan': No scheme supplied. Perhaps you meant https://nan?
Error loading image from nan: Invalid URL 'nan': No scheme supplied. Perhaps you meant https://nan?
Error loading image from nan: Invalid URL 'nan': No scheme supplied. Perhaps you meant https://nan?
Error loading image from nan: Invalid URL 'nan': No scheme supplied. Perhaps you meant https://nan?
Error loading image from nan: Invalid URL 'nan': No scheme supplied. Perhaps you meant https://nan?
Error loading image from nan: Invalid URL 'nan': No scheme supplied. Perhaps you meant https://nan?
Error loading image from nan: Invalid URL 'nan': No scheme supplied. Perhaps you meant https://nan?
Error loading image from nan: Invalid URL 'nan': No scheme supplied. Perhaps you meant https://nan?
Error loading image from nan: Invalid URL 'nan': No scheme supplied. Perhaps you meant https://nan?
Error loading image from nan: Invalid URL 'nan': No scheme supplied. Perhaps you meant https://nan?
Error loading image from nan: Invalid URL 'nan': No scheme supplied. Perhaps you meant https://nan?
Error loading image from nan: Invalid URL 'nan': No scheme supplied. Perhaps you meant https://nan?
Error loading image from nan: Invalid URL 'nan': No scheme supplied. Perhaps you meant https://nan?
Error loading image from nan: Invalid URL 'nan': No scheme supplied. Perhaps you meant https://nan?
Error loading image from nan: Invalid URL 'nan': No scheme supplied. Perhaps you meant https://nan?
Error loading image from nan: Invalid URL 'nan': No scheme supplied. Perhaps you meant https://nan?
Error loading image from nan: Invalid URL 'nan': No scheme supplied. Perhaps you meant https://nan?
Error loading image from nan: Invalid URL 'nan': No scheme supplied. Perhaps you meant https://nan?
Error loading image from nan: Invalid URL 'nan': No scheme supplied. Perhaps you meant https://nan?
Error loading image from nan: Invalid URL 'nan': No scheme supplied. Perhaps you meant https://nan?
Error loading image from nan: Invalid URL 'nan': No scheme supplied. Perhaps you meant https://nan?
Error loading image from nan: Invalid URL 'nan': No scheme supplied. Perhaps you meant https://nan?

import matplotlib.pyplot as plt
import requests
from PIL import Image
from io import BytesIO

def plot_images_from_urls(url_list):
    fig, axes = plt.subplots(nrows=len(url_list), ncols=1, figsize=(5, 5 * len(url_list)))

    for i, url in enumerate(url_list):
        try:
            response = requests.get(url)
            response.raise_for_status()  # Raise exception for bad status codes
            img = Image.open(BytesIO(response.content))
            axes[i].imshow(img)
            axes[i].axis('off')  # Hide axis ticks and labels
        except Exception as e:
            print(f"Error loading image from {url}: {e}")

    plt.tight_layout()
    plt.show()


url_list = BCE_URL #intercgnage the URL list to the century list of URLS
plot_images_from_urls(url_list)

Output hidden; open in https://colab.research.google.com to view.

!pip install nbconvert

Requirement already satisfied: nbconvert in /usr/local/lib/python3.10/dist-packages (7.16.4)
Requirement already satisfied: beautifulsoup4 in /usr/local/lib/python3.10/dist-packages (from nbconvert) (4.12.3)
Requirement already satisfied: bleach!=5.0.0 in /usr/local/lib/python3.10/dist-packages (from nbconvert) (6.2.0)
Requirement already satisfied: defusedxml in /usr/local/lib/python3.10/dist-packages (from nbconvert) (0.7.1)
Requirement already satisfied: jinja2>=3.0 in /usr/local/lib/python3.10/dist-packages (from nbconvert) (3.1.4)
Requirement already satisfied: jupyter-core>=4.7 in /usr/local/lib/python3.10/dist-packages (from nbconvert) (5.7.2)
Requirement already satisfied: jupyterlab-pygments in /usr/local/lib/python3.10/dist-packages (from nbconvert) (0.3.0)
Requirement already satisfied: markupsafe>=2.0 in /usr/local/lib/python3.10/dist-packages (from nbconvert) (3.0.2)
Requirement already satisfied: mistune<4,>=2.0.3 in /usr/local/lib/python3.10/dist-packages (from nbconvert) (3.0.2)
Requirement already satisfied: nbclient>=0.5.0 in /usr/local/lib/python3.10/dist-packages (from nbconvert) (0.10.1)
Requirement already satisfied: nbformat>=5.7 in /usr/local/lib/python3.10/dist-packages (from nbconvert) (5.10.4)
Requirement already satisfied: packaging in /usr/local/lib/python3.10/dist-packages (from nbconvert) (24.2)
Requirement already satisfied: pandocfilters>=1.4.1 in /usr/local/lib/python3.10/dist-packages (from nbconvert) (1.5.1)
Requirement already satisfied: pygments>=2.4.1 in /usr/local/lib/python3.10/dist-packages (from nbconvert) (2.18.0)
Requirement already satisfied: tinycss2 in /usr/local/lib/python3.10/dist-packages (from nbconvert) (1.4.0)
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from google.colab import drive
drive.mount('/content/drive')

Drive already mounted at /content/drive; to attempt to forcibly remount, call drive.mount("/content/drive", force_remount=True).

%cd '/content/drive/My Drive/'

/content/drive/My Drive

!jupyter nbconvert --to html your_notebook.ipynb

	count
department
Drawings and Prints	98
The Michael C. Rockefeller Wing	17
Egyptian Art	15
Photographs	15
Greek and Roman Art	10
Asian Art	9
European Sculpture and Decorative Arts	9
The American Wing	6
Modern and Contemporary Art	5
European Paintings	3
Musical Instruments	2
Robert Lehman Collection	2
Ancient Near Eastern Art	1
Islamic Art	1

	count
country
	159
Egypt	11
Peru	3
France	2
Mexico	2
Costa Rica	2
Ghana	2
South Africa	2
Ethiopia	2
Australia	1
Iran	1
Italy?	1
Colombia	1
Western Australia	1
United States	1
Ecuador	1
Germany	1

	count
date
ca. 1920	12
ca. 1910	6
1968, printed later	5
1968	5
19th century	4
	3
April 28, 1938	3
1884	3
1646	2
3rd–6th century	2
1635	2
1665	2
1st century BCE–1st century CE	2
1966	2
January 24, 1784	2
1760 (?)	2
1563	2
October 25, 1810	2
1812	2
April 1, 1790	2
1810–20	2
May 1, 1803	2
July 12, 1808	2
664–30 B.C.	2
ca. 540–530 BCE	2
19th–20th century	2
1764–70	2
1936	1
1919	1
1870–74	1
1868–78	1
3rd–4th century CE	1
5th–1st century BCE	1
ca.3300–3100 0 B.C.	1
1983	1
1824	1
1872	1
ca. 1920–1960	1
May 6, 1807	1
1960s–70s	1
ca. 1932	1
7th–8th century	1
1873	1
April 4, 1798	1
ca. 1741	1
20th century	1
ca. 1917	1
early 4th century BCE	1
March 3, 1789	1
late 16th century	1
late 17th century	1
ca. 1912	1
1875	1
1887	1
1655	1
1857–1872	1
early 15th century	1
1756–57	1
1778–80	1
1870	1
May 1, 1790	1
December 8, 1776	1
December 26, 1776	1
mid-12th century	1
[1790] reissue April 1, 1796	1
ca. 1695	1
1885	1
1877	1
ca.1640–1660	1
1500–10	1
1769	1
ca. 1815	1
ca. 9th–8th century BCE	1
May 1, 1788	1
late 19th–early 20th century	1
ca. 750	1
1870s	1
1947	1
1650	1
1943	1
1990	1
1820–22	1
1989	1
2nd quarter of the 6th century BCE	1
ca. 2107–2103 B.C.	1
ca. 1349–1327 BC	1
June 19, 1865	1
ca. 1492–1473 B.C.	1
1964	1
ca. 1510–27	1
18th century	1
ca. 1981–1975 B.C.	1
ca. 1336–1295 B.C.	1
1729	1
ca. 1776	1
100–400 CE	1
1982	1
1905	1
380–343 B.C.	1
late 1st century BCE	1
ca. 1763	1
ca. 1800–1650 B.C.	1
ca. 1702	1
ca. 3450–3300 B.C.	1
1750	1
ca. 1981–1952 B.C.	1
2020	1
dated 1652	1
17th century	1
1565	1
ca. 1504–1425 B.C.	1
9th–4th century BCE	1
1970, printed later	1
1924	1
332–30 B.C.	1
early 3rd century CE	1
1st–5th century	1
ca. 1827	1
1817	1
1820	1
ca. 69–79 CE	1
mid-16th century	1
ca. 3rd century CE	1
ca. 1866	1
1974–78	1
1432	1
1830 or later	1
ca. 1780–90	1
ca. 1840	1
1200–800 BCE	1
ca. 1633–34	1
late 15th–early 16th century	1
January 1554	1
November 26, 1867	1
1867	1
1882	1
ca. 1390–1352 B.C.	1
1780–90	1
1960, printed later	1
January 1, 1799	1
1869	1

	count
date
1920.0	12
1968.0	10
1910.0	6
1790.0	4
1800.0	4
1776.0	3
1884.0	3
1650.0	3
1938.0	3
1815.0	3
1803.0	2
1900.0	2
1784.0	2
1785.0	2
1966.0	2
1812.0	2
1808.0	2
1810.0	2
1760.0	2
1850.0	2
1867.0	2
1870.0	2
1872.0	2
1873.0	2
1767.0	2
1.0	2
1635.0	2
200.0	2
-647.0	2
350.0	2
-550.0	2
1665.0	2
-535.0	2
1563.0	2
1646.0	2
-1371.0	1
1947.0	1
1943.0	1
1940.0	1
-331.0	1
1936.0	1
-3375.0	1
-361.0	1
1932.0	1
1924.0	1
1964.0	1
1919.0	1
1917.0	1
1912.0	1
-750.0	1
1960.0	1
-250.0	1
-325.0	1
1982.0	1
-1315.0	1
-1000.0	1
2020.0	1
1990.0	1
-1464.0	1
1989.0	1
-1482.0	1
1983.0	1
-1725.0	1
-3200.0	1
1976.0	1
1970.0	1
-1966.0	1
-1978.0	1
-200.0	1
1965.0	1
-2105.0	1
-1338.0	1
1905.0	1
1865.0	1
1887.0	1
1885.0	1
1741.0	1
1729.0	1
1702.0	1
1700.0	1
1695.0	1
1690.0	1
1655.0	1
1633.0	1
1565.0	1
1554.0	1
1550.0	1
1518.0	1
1505.0	1
1500.0	1
1432.0	1
1425.0	1
1150.0	1
750.0	1
650.0	1
250.0	1
225.0	1
1750.0	1
1756.0	1
1763.0	1
1827.0	1
1882.0	1
1877.0	1
1875.0	1
1869.0	1
1866.0	1
74.0	1
1864.0	1
1840.0	1
1830.0	1
1824.0	1
1769.0	1
1821.0	1
1820.0	1
1817.0	1
1807.0	1
1799.0	1
1798.0	1
1789.0	1
1788.0	1
1779.0	1
-90.0	1

	date
count	188.000000
mean	1340.569149
std	1089.459916
min	-3375.000000
25%	1616.000000
50%	1805.000000
75%	1910.000000
max	2020.000000

	title	name	medium	date	country	image_url	objectURL	department
0	Hieratic Jar Label		Pottery	ca. 1390–1353 B.C.	Egypt	https://images.metmuseum.org/CRDImages/eg/orig...	https://www.metmuseum.org/art/collection/searc...	Egyptian Art
1	Bowl of Fat		Pottery, fat	ca. 1479–1458 B.C.	Egypt	https://images.metmuseum.org/CRDImages/eg/orig...	https://www.metmuseum.org/art/collection/searc...	Egyptian Art
2	Jar Label		Pottery, ink	ca. 1390–1352 B.C.	Egypt		https://www.metmuseum.org/art/collection/searc...	Egyptian Art
3	Jar Label		Pottery, ink	ca. 1390–1352 B.C.	Egypt		https://www.metmuseum.org/art/collection/searc...	Egyptian Art
4	Gilt bronze ring		Bronze, gold	early 4th century BCE		https://images.metmuseum.org/CRDImages/gr/orig...	https://www.metmuseum.org/art/collection/searc...	Greek and Roman Art
...	...	...	...	...	...	...	...	...
267	Redemption – Repudiation : Prosperity – Ruin	Currier & Ives	Lithograph	1875			https://www.metmuseum.org/art/collection/searc...	Drawings and Prints
268	None	None	None	None	None	None	None	None
269	September Morn	Paul Chabas	Oil on canvas	ca. 1912			https://www.metmuseum.org/art/collection/searc...	Modern and Contemporary Art
270	Prayer Book: Arganonä Maryam (The Organ of Mary)	Baselyos (The Ground Hornbill Master)	Parchment, pigment ink, wood, leather, fiber	late 17th century	Ethiopia	https://images.metmuseum.org/CRDImages/ao/orig...	https://www.metmuseum.org/art/collection/searc...	The Michael C. Rockefeller Wing
271	Jack in Office	Sir Edwin Henry Landseer	Color process	1869			https://www.metmuseum.org/art/collection/searc...	Drawings and Prints

	count
medium
Gelatin silver print	12
Commercial color lithograph reproducing drawing	12
Hand-colored etching	11
Etching	10
Oil on canvas	5
Commercial lithograph	5
Lithograph	4
Ceramic, pigment	3
Hand-colored etching and aquatint	3
Limestone	3
Wood	3
Terracotta	3
Cupreous metal	3
Ivory	3
Commercial color lithograph	3
Hand-colored lithograph	3
Glass	3
Film negative	3
Gold	3
Etching; only state	2
Engraving	2
Etching; second state of three (Lieure)	2
Pen and black ink, gray wash	2
Etching; second state	2
Etching; first state of three	2
Hand-colored etching and stipple	2
Ceramic, slip	2
Bronze	2
Lithograph, printed in color	2
Etching; third state	2
Etching and stipple	1
Carved Australian Gold-Lipped Pearl Shell, Pinctada Maxima [not endangered], natural earth pigments, human hair	1
Terracotta; marble	1
Ink, graphite, and crayon on heavy cream board/card	1
Engraving; first state	1
Etching and engraving	1
Pottery	1
Wood, beads, string	1
Pen, iron-gaul ink and graphite on off-white laid paper	1
Hand-colored etching and aquatint; second state	1
Jade (jadeite)	1
Bronze, gold	1
Pen and brown ink with pen and black ink and brush and gray wash. Composition outlined in pen and brown ink. Contours incised and verso blackened with carbon dust for transfer	1
Woodcut	1
Hand-colored lithograph with gum arabic	1
Parchment, pigment ink, wood, leather, fiber	1
Handscroll; ink, color, and gold on silk	1
Illustrations: woodcut	1
Etching; after third state	1
Ink and watercolor on paper	1
Handscroll; ink and color on silk	1
Album of twelve leaves; ink and color on paper	1
Lithograph printed in color	1
Etching on blue paper	1
Oil on slate paper	1
Lithograph printed in color with gum arabic	1
Tempera on wood	1
Parchment (vellum), pigment (red, blue, ochre, and black), leather, wood, string	1
Pen and black ink, brush and gray wash, over black chalk	1
Heavy card stock, lithography, watercolor, thread	1
Pearl shell, human hair, ocher	1
Photomechanical reproduction	1
Handscroll; ink on paper	1
Cardboard (cover)\r\nDrawings in ink, wash, and graphite on light brown laid paper with fibers of mixed composition (sheets)	1
Cotton	1
Frieze of seven woodcuts plus title printed on Toshi paper with a woodcut cover printed on thick oatmeal paper	1
Bronze, ivory	1
Cartonnage, gold, travertine (Egyptian alabaster), obsidian, ebony	1
Pen and black ink	1
Brush and gray wash, over graphite	1
Plastered and painted wood, gesso	1
Oak veneered with tulipwood, amaranth, holly, and sycamore; six Sèvres soft-paste porcelain plaques and two painted tin plaques; gilt-bronze mounts; marble shelves; moiré silk	1
Mahogany, maple, rosewood, metal, plastic	1
Greywacke	1
Pair of six-panel folding screens; ink and color on paper	1
Fine-grained grey stone (graywacke?)	1
Oil and gold on copper	1
Limestone, organic material, paint, malachite	1
Etching, between second and third states	1
Granite	1
Glazed ceramic	1
Album of four leaves; ink and color on silk	1
Mutton fat jade	1
Nephrite, a mottling of lettuce- and emerald-green, interspersed with small patches of greenish-gray; upon one side a very large patch of color resembling mutton-fat in which there are delicate veinings of brown	1
Lithograph on newsprint; second state of two (Delteil)	1
Gouache, tempera, and cut, torn, and pasted painted papers on paper	1
Wood, beads, fiber	1
Sugar lift aquatint	1
Jadeite	1
Marble	1
Pen and ink on lined blue paper	1
Wood engraving; working proofs	1
High-copper alloy, fire-gilt, brown natural patina where exposed	1
Carved and painted basswood, glass and gilded-bronze mounts	1
Ceramic, cinnabar, red ochre	1
Hand-colored etching and stipple, printed in brown ink	1
Bronze, silver inlay (eyes), on a later porphyry and ormolu base	1
	1
Lithograph and pen and brown ink on newsprint; third state of three, proof (Delteil)	1
Wood engraving	1
Etching on laid paper; second state of two	1
Pottery and ink	1
Etching, printed in brown ink	1
Paper, tempera paint, ink	1
Engraving; first state of three	1
Color process	1

	title	name	medium	date	country	image_url	objectURL	department
count	193	193	193	193	193	193	193	193
unique	164	83	106	141	17	102	193	14
top	Trade card from the Fat and Skinny Their Littl...		Gelatin silver print	ca. 1920			https://www.metmuseum.org/art/collection/searc...	Drawings and Prints
freq	12	58	12	12	159	92	1	98

	title	name	medium	date	country	image_url	objectURL	department
163	Seated hollow figure with helmet	Las Bocas artist(s)	Ceramic	-1000.0	Mexico	https://images.metmuseum.org/CRDImages/ao/orig...	https://www.metmuseum.org/art/collection/searc...	The Michael C. Rockefeller Wing
164	Relief of Hatiay	NaN	Limestone	-1315.0	Egypt	https://images.metmuseum.org/CRDImages/eg/orig...	https://www.metmuseum.org/art/collection/searc...	Egyptian Art
165	Relief Depicting Meryneith Inspecting His Stab...	NaN	Limestone	-1338.0	Egypt	https://images.metmuseum.org/CRDImages/eg/orig...	https://www.metmuseum.org/art/collection/searc...	Egyptian Art
166	Fragment of a labeled jar containing fat	NaN	Pottery and ink	-1371.0	Egypt	NaN	https://www.metmuseum.org/art/collection/searc...	Egyptian Art
167	Cooking Cakes with Fat, Tomb of Rekhmire	Nina de Garis Davies	Paper, tempera paint, ink	-1464.0	Egypt	https://images.metmuseum.org/CRDImages/eg/orig...	https://www.metmuseum.org/art/collection/searc...	Egyptian Art
168	Funerary mask of Hatnefer	NaN	Cartonnage, gold, travertine (Egyptian alabast...	-1482.0	Egypt	https://images.metmuseum.org/CRDImages/eg/orig...	https://www.metmuseum.org/art/collection/searc...	Egyptian Art
169	Upper part of a male seated figure	NaN	Fine-grained grey stone (graywacke?)	-1725.0	Egypt	https://images.metmuseum.org/CRDImages/eg/orig...	https://www.metmuseum.org/art/collection/searc...	Egyptian Art
170	Offering table from the mortuary temple of Ame...	NaN	Granite	-1966.0	Egypt	https://images.metmuseum.org/CRDImages/eg/orig...	https://www.metmuseum.org/art/collection/searc...	Egyptian Art
171	Model Cattle stable from the tomb of Meketre	NaN	Plastered and painted wood, gesso	-1978.0	Egypt	https://images.metmuseum.org/CRDImages/eg/orig...	https://www.metmuseum.org/art/collection/searc...	Egyptian Art
172	Funerary Mask	NaN	Gold	-200.0	Colombia	https://images.metmuseum.org/CRDImages/ao/orig...	https://www.metmuseum.org/art/collection/searc...	The Michael C. Rockefeller Wing
173	Fragment of decree of Horus Khabau, probably K...	NaN	Limestone	-2105.0	Egypt	https://images.metmuseum.org/CRDImages/eg/orig...	https://www.metmuseum.org/art/collection/searc...	Egyptian Art
174	Drum	Nasca artist(s)	Ceramic	-250.0	Peru	https://images.metmuseum.org/CRDImages/ao/orig...	https://www.metmuseum.org/art/collection/searc...	The Michael C. Rockefeller Wing
175	Wavy-handled jar	NaN	Pottery	-3200.0	Egypt	https://images.metmuseum.org/CRDImages/eg/orig...	https://www.metmuseum.org/art/collection/searc...	Egyptian Art
176	Gilt bronze ring	NaN	Bronze	-325.0	Greek/Roman	https://images.metmuseum.org/CRDImages/gr/orig...	https://www.metmuseum.org/art/collection/searc...	Greek and Roman Art
177	Statuette of Harpokrates	NaN	Cupreous metal	-331.0	Egypt	https://images.metmuseum.org/CRDImages/eg/orig...	https://www.metmuseum.org/art/collection/searc...	Egyptian Art
178	Figurine of a Seated Woman	NaN	Limestone, organic material, paint, malachite	-3375.0	Egypt	NaN	https://www.metmuseum.org/art/collection/searc...	Egyptian Art
179	Bust of an Official	NaN	Greywacke	-361.0	Egypt	https://images.metmuseum.org/CRDImages/eg/orig...	https://www.metmuseum.org/art/collection/searc...	Egyptian Art
180	Statuette of a fat boy (dwarf ?)	NaN	Terracotta	-535.0	Greek/Roman	NaN	https://www.metmuseum.org/art/collection/searc...	Greek and Roman Art
181	Terracotta aryballos (perfume vase) in the for...	NaN	Terracotta	-535.0	Greek/Roman	https://images.metmuseum.org/CRDImages/gr/orig...	https://www.metmuseum.org/art/collection/searc...	Greek and Roman Art
182	Bronze chariot inlaid with ivory	NaN	Bronze	-550.0	Greek/Roman	https://images.metmuseum.org/CRDImages/gr/orig...	https://www.metmuseum.org/art/collection/searc...	Greek and Roman Art
183	Figure Vessel	NaN	Ceramic	-550.0	Ecuador	https://images.metmuseum.org/CRDImages/ao/orig...	https://www.metmuseum.org/art/collection/searc...	The Michael C. Rockefeller Wing
184	Child god wearing Amonian crown and named Horu...	NaN	Cupreous metal	-647.0	Egypt	https://images.metmuseum.org/CRDImages/eg/orig...	https://www.metmuseum.org/art/collection/searc...	Egyptian Art
185	Isis and Horus	NaN	Cupreous metal	-647.0	Egypt	https://images.metmuseum.org/CRDImages/eg/orig...	https://www.metmuseum.org/art/collection/searc...	Egyptian Art
186	Openwork furniture plaque showing a cow suckli...	NaN	Ivory	-750.0	NaN	https://images.metmuseum.org/CRDImages/an/orig...	https://www.metmuseum.org/art/collection/searc...	Ancient Near Eastern Art
187	Bronze statuette of a philosopher on a lamp stand	NaN	Bronze	-90.0	Greek/Roman	https://images.metmuseum.org/CRDImages/gr/orig...	https://www.metmuseum.org/art/collection/searc...	Greek and Roman Art

	title	name	medium	date	country	image_url	objectURL	department
0	Bird Pendant	NaN	Jade (jadeite)	1.0	Costa Rica	https://images.metmuseum.org/CRDImages/ao/orig...	https://www.metmuseum.org/art/collection/searc...	The Michael C. Rockefeller Wing
1	Terracotta oil lamp	NaN	Terracotta	1.0	Greek/Roman	https://images.metmuseum.org/CRDImages/gr/orig...	https://www.metmuseum.org/art/collection/searc...	Greek and Roman Art
2	Marble portrait bust of a man	NaN	Marble	74.0	Greek/Roman	https://images.metmuseum.org/CRDImages/gr/orig...	https://www.metmuseum.org/art/collection/searc...	Greek and Roman Art

	Century	Most Frequent Medium	Freq
0	BCE	Ceramic	3
1	1st Century	Jade (jadeite)	1
2	3rd Century	Glass	3
3	4th Century	Ceramic	2
4	7th Century	Ceramic	1
5	8th Century	Handscroll; ink	1
6	12th Century	Handscroll; ink	1
7	15th Century	Handscroll; ink	1
8	16th Century	Engraving	3
9	17th Century	Etching	9
10	18th Century	Etching	17
11	19th Century	Lithograph	14
12	20th Century	Lithograph	20
13	21st Century	Ceramic	1